With the widespread implementation of robotics exoskeletons in rehabilitation, modeling and dynamics analysis of such highly nonlinear coupled systems has become significantly important. In this paper, a swift numerical human–robot dynamics modeling has been developed to achieve accurate and realistic interpretation. This takes into consideration the separation and impact between multiple bodies for rehabilitation planning. To this end, first, a novel parallel algorithm combined with sequential interaction conditions is proposed based on the numerical recursive Newton–Euler method. The approach begins by deriving separated numerical models for the complicated system: i.e. both the human and the robot. These models are then augmented, with a primary focus on reducing the error of the interaction conditions, including forces and positions. The accuracy of the proposed model, with a computational complexity of O(n), is assessed by comparing to a previously validated nonrecursive analytical model with a higher computational complexity of O(n^4). Additionally, the quality of the connection between the human and the robot is assessed to establish a suitable control objective and an effective interaction strategy for rehabilitation planning. The study employs a lower-limb walking assistive robot developed in the ARAS lab (RoboWalk) to validate the proposed method. The algorithm is empirically implemented on the RoboWalk test stand, ensuring the integrity of the proposed dynamics modeling. The human–robot interaction forces are estimated with an accuracy of 2 N, in the presence of friction and measurement noise. Finally, the effectiveness of the model-based controller is assessed by using the proposed method, providing valuable tools for the enhancement of overall performance of such a complex dynamics system.

随着机器人外骨骼在康复领域的广泛应用，这种高度非线性耦合系统的建模和动力学分析变得非常重要。在本文中，开发了一种快速数值人机动力学模型，以实现准确和现实的解释。这考虑到了多个康复规划机构之间的分离和影响。为此，首先，基于数值递归牛顿欧拉方法，提出了一种结合顺序交互条件的新型并行算法。该方法首先为复杂系统（即人类和机器人）导出单独的数值模型。然后对这些模型进行增强，主要关注减少相互作用条件（包括力和位置）的误差。通过与先前验证的具有较高计算复杂度 O(n^4) 的非递归分析模型进行比较，评估所提出的模型的准确性（计算复杂度为 O(n)）。此外，还评估人与机器人之间的连接质量，以便为康复规划建立合适的控制目标和有效的交互策略。该研究采用 ARAS 实验室开发的下肢步行辅助机器人（RoboWalk）来验证所提出的方法。该算法在 RoboWalk 测试台上进行了实证实施，确保了所提出的动力学建模的完整性。在存在摩擦和测量噪声的情况下，人机交互力的估计精度为 2 N。最后，使用所提出的方法评估基于模型的控制器的有效性，为提高这种复杂动态系统的整体性能提供有价值的工具。